出血性脑卒中患者血压精准重症管理数据集

用于出血性脑卒中患者个体化血压管理的动态线性模型数据集,包含模拟血压时间序列,支持精准重症监护研究。

Figshare
2019-08-05 更新
浏览 19
时间序列AIM-BP parameter estimatorframeworkAcute Intervention Modelblood pressurehomeostasis perturbation modellikelihood estimation methodhemorrhagic stroke patients
Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models

基本信息

模态
时间序列
大小
0.001351144 GB
许可
CC BY 4.0
创建/更新时间
2019-08-05
版本
v1

资源简介

出血性脑卒中患者血压精准重症管理数据集

【数据集背景】

本数据集源站标题为《Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models》。配套论文《Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models》发表于 PLOS ONE(2019),DOI:10.1371/journal.pone.0220283。源站首次发布:2019-08-05。

【数据内容】

源站原始描述:Finding optimal blood pressure (BP) target and BP treatment after acute ischemic or hemorrhagic strokes is an area of controversy and a significant unmet need in the critical care of stroke victims. Numerous large prospective clinical trials have been done to address this question but have generated neutral or conflicting results. One major limitation that may have contributed to so many neutral or conflicting clinical trial results is the “one-size fit all” approach to BP targets, while the opt…

【数据结构与技术规格】

文件数 10 个,合计 1.35 MB。pone.0220283.s001.pdf:application/pdf,36.52 KB。pone.0220283.s002.pdf:application/pdf,62.30 KB。pone.0220283.s003.pdf:application/pdf,94.82 KB。数据集 DOI:10.1371/journal.pone.0220283。

【主题与分类】

源站学科分类:Medicine、Neuroscience、Environmental Sciences not elsewhere classified、Ecology、Biological Sciences not elsewhere classified、Mathematical Sciences not elsewhere classified。主题标签:AIM-BP parameter estimator、framework、Acute Intervention Model、blood pressure、homeostasis perturbation model、likelihood estimation method、hemorrhagic stroke patients。

【适用方向】

时序数据适用于疾病进展预测、生理信号监测与事件发生的时序建模。

【获取与许可】

源站页面:https://plos.figshare.com/articles/dataset/Towards_precision_critical_care_management_of_blood_pressure_in_hemorrhagic_stroke_patients_using_dynamic_linear_models/9250952

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Liu, Yuzhe; Manners, Jody; Bittar, Yazan; Chou, Sherry H-Y.; Gopalakrishnan, Vanathi (2019). Towards precision critical care management of blood pressure in hemorrhagic stroke patients using dynamic linear models. PLOS ONE. Dataset

【使用注意】

· 源站最后修改于 2023-06-03,引用时请注意版本时效。

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下载信息

注册下载

需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。

暂未开放

公开下载

无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。

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有偿下载

公开数据集受托下载与技术交付服务。

提供高速下载与技术交付服务(收技术服务费,非数据销售)

暂未开放

当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。

使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "pone.0220283.s001.pdf" "https://ndownloader.figshare.com/files/16841528"
curl -L -o "pone.0220283.s002.pdf" "https://ndownloader.figshare.com/files/16841531"
curl -L -o "pone.0220283.s003.pdf" "https://ndownloader.figshare.com/files/16841534"
curl -L -o "pone.0220283.s004.pdf" "https://ndownloader.figshare.com/files/16841537"
curl -L -o "pone.0220283.s005.tiff" "https://ndownloader.figshare.com/files/16841540"
curl -L -o "pone.0220283.s006.tiff" "https://ndownloader.figshare.com/files/16841543"
curl -L -o "pone.0220283.s007.tiff" "https://ndownloader.figshare.com/files/16841546"
curl -L -o "pone.0220283.s008.tiff" "https://ndownloader.figshare.com/files/16841549"

文件清单

  • pone.0220283.s001.pdf(36.52 KB)
  • pone.0220283.s002.pdf(62.30 KB)
  • pone.0220283.s003.pdf(94.82 KB)
  • pone.0220283.s004.pdf(72.49 KB)
  • pone.0220283.s005.tiff(181.45 KB)
  • pone.0220283.s006.tiff(178.27 KB)
  • pone.0220283.s007.tiff(138.54 KB)
  • pone.0220283.s008.tiff(137.58 KB)
  • pone.0220283.s009.tiff(223.45 KB)
  • pone.0220283.s010.tiff(225.72 KB)

文件总体积 1.35 MB(源站 API 实测)。

数据说明

Finding optimal blood pressure (BP) target and BP treatment after acute ischemic or hemorrhagic strokes is an area of controversy and a significant unmet need in the critical care of stroke victims. Numerous large prospective clinical trials have been done to address this question but have generated neutral or conflicting results. One major limitation that may have contributed to so many neutral or conflicting clinical trial results is the “one-size fit all” approach to BP targets, while the optimal BP target likely varies between individuals. We address this problem with the Acute Intervention Model of Blood Pressure (AIM-BP) framework: an individualized, human interpretable model of BP and its control in the acute care setting. The framework consists of two components: one, a model of BP homeostasis and the various effects that perturb it; and two, a parameter estimator that can learn clinically important model parameters on a patient by patient basis. By estimating the parameters of the AIM-BP model for a given patient, the effectiveness of antihypertensive medication can be quantified separately from the patient’s spontaneous BP trends. We hypothesize that the AIM-BP is a sufficient framework for estimating parameters of a homeostasis perturbation model of a stroke patient’s BP time course and the AIM-BP parameter estimator can do so as accurately and consistently as a state-of-the-art maximum likelihood estimation method. We demonstrate that this is the case in a proof of concept of the AIM-BP framework, using simulated clinical scenarios modeled on stroke patients from real world intensive care datasets.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0220283(source: https://plos.figshare.com/articles/dataset/Towards_precision_critical_care_management_of_blood_pressure_in_hemorrhagic_stroke_patients_using_dynamic_linear_models/9250952)。

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